6

This chapter provides an introduction to the problems of generalization and transportation and methods for addressing these concerns. The field of causal inference is one that, at its core, focuses on improving internal validity--the extent to which a study can establish a trustworthy cause-and-effect relationship between a treatment and outcome. To understand potential external validity bias,...

Experiments have come to be a widely accepted and highly regarded method for political science research. Randomization allows for well identified causal effects that are "internally valid" to the experimental setting. However, political scientists are driven by asking big questions with broad impacts...

This chapter focuses on methods for analyzing data from Internet surveys with complex survey designs in order to draw inferences that can be generalized to a target population of interest...